OntoPaRON

OntoPaRON analyzes care pathways of amyotrophic lateral sclerosis (ALS) patients within the Ile-de-France ALS network by applying a modular ontology and the OnBaSAM semantic annotation to French clinical texts to extract structured quantitative data for pathway analysis.

Key Features:

• Modular Ontology Structure: A modular ontology comprising five modules—core, medical, socio-environmental, coordination, and consolidation—captures distinct aspects of healthcare trajectories.
• Ontology-Based Semantic Annotation (OnBaSAM): OnBaSAM performs semantic annotation of unstructured French clinical text using the OntoPaRON ontology as its reference.
• Processing of Real-Life Clinical Texts: The system processes unstructured patient records from real-life clinical sources within the regional network.
• Automatic Annotation at Cohort Scale: OntoPaRON automatically annotated records from 928 patients in the described cohort.
• Quantitative Transformation: Qualitative semantic annotations are converted into structured quantitative datasets suitable for downstream analysis.
• Analytical Outputs: Integrated analysis with sociodemographic and clinical variables identifies dependencies of human and technical assistance needs on disease form, motor state, and patient age, and correlations between care management exhaustion and motor and cognitive states.

Scientific Applications:

• Care Pathway Analysis: Generation of structured datasets from unstructured clinical text to study and describe ALS patient care trajectories within a coordination network.
• Clinical and Epidemiological Research: Investigation of relationships between disease form, motor and cognitive state, age, and requirements for human and technical assistance.
• Identification of Care Management Correlates: Detection of correlations between care management exhaustion and patients' motor and cognitive conditions to inform targeted research and planning.

Methodology:

OntoPaRON uses a modular ontology and the OnBaSAM semantic annotation module (referencing the OntoPaRON ontology) to automatically annotate French clinical records (928 patients) and convert qualitative semantic annotations into structured quantitative datasets integrated with sociodemographic and clinical variables for analysis.